• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.183-193
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• 2019

This study developed a shockwave detection and prediction of their extinction point method based on continuous wavelet transform using trajectory data from probe vehicles equipped with automotive sensors.. To analyze the effectiveness of the proposed method, this paper proposed two measures which are a distance error between the extinction points of the predictor and an time-location error of the extinction points. The proposed concept was proved using the micro simulation based experiment with three exogenous variables of traffic volume, lane-close duration, market penetration of probe vehicles. The analysis results show that the proposed method is capable of detecting the traffic shockwaves as well as predicting their extinction point, and also that the accuracy of the proposed method is highly dependent on the rate of the probe vehicles.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.194-199
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• 2019

Natural disasters destroy decades of human effort and investments, thereby placing new demands on society for reconstruction and rehabilitation. In most case, the natural phenomena triggering the disasters are beyond human control. In order to solve the problems that the information resources can not be shared among disaster management sectors and their work is hard to be coordinated in city, an idea of application of ubiquitous sense network and ICT technology to model the architecture of the disaster prevention system based on the analysis of characteristics of disasters. The proposed algorithm simulated that it is possible to locate the terminal by linking the direction angle and the estimated position that can be confirmed at the time of stopping, even if the movement direction of the terminal does not move in a certain direction with only a smaller number of mobile base stations. We also confirmed that the proposed algorithms analyzed through simulation are more efficient than existing algorithms.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.267-275
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• 2021

Smart application is developed in this paper by using an android-based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain.

• Atmosphere
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• v.32 no.4
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• pp.307-322
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• 2022

A drone has recently got attention as an instrument for weather observation in lower atmosphere because it can produce the high spatiotemporal resolution weather data even though the weather phenomenon is inaccessible. Sea fog is a weather phenomenon occurred in lower atmosphere, and has observational limitations because it occurs on the sea. Therefore, goal of this study is to analyze the vertical structures about inflow, development and dispersion of sea fog using the high-resolution weather data with the meteorological sensor-equipped drone. This study observed sea fogs in the west coast of the Korean peninsula from March to October 2021 and investigated one sea fog inflowed into the coast on June 8th 2021. θ_e - q_v diagrams (θ_e: equivalent potential temperature, q_v: water vapor ratio) and vertical wind structures were analyzed. At inflow of sea fog, moist adiabatically stable layer was formed in 0-300 m and prevailing wind was switched from south-southwesterly to west-southwesterly under 120 m. Both changes are favorable for sea fog on the location. θ_e and q_v plummeted in a layer 0-183 m. The inflowed sea fog developed from 183 m to 327 m by mixing with ambient atmosphere on top of sea fog. Also, strong mechanical turbulence near ground drove a vertical mixing under stable layer. At dispersion of sea fog, as θ_e on ground gradually increased, air condition was changed to neutral. Evaporation occurred on both bottom and top in sea fog. These results induced dissipation of sea fog.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.786-791
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• 2021

In this paper, in order to minimize limitations such as signal interference and positioning errors in existing indoor positioning systems, a smart LED-based positioning system for excellent line-of-sight radio environments and precise location tracking is proposed to improve accuracy. An IEEE 802.4 Zigbee module is mounted on the SMPS board of a smart LED; RSSI and LQI signals are received from a moving tag, and the system is configured to transmit the measured data to the positioning server through a gateway. For the experiment, the necessary hardware, such as the gateway and the smart LED module, were separately designed, and the experiment was conducted after configuring the system in an external field office. The positioning error was within 70cm as a result of performing complex calculations in the positioning server after transmitting a vector value of the moving object obtained from the direction sensor, together with a signal from the moving object received by the smart LED. The result is a significantly improved positioning error, compared to an existing short-range wireless communications-based system, and shows the level at which commercial products can be implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1519-1527
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• 2020

AGeneral radiation measuring devices have been developed in the form of spatial dose rate detection devices that measure dose rates to radioactive contaminant and 2D or 3D imaging devices for radioactive contamination information. Each of these radiation detection techniques has advantages. The advantages of both detection devices are necessary to minimize personal injury and rapid decontamination in the area of a radioactive accident. In this paper, we proposed a technique that can measure the dose rate and direction information about the radioactive pollutant source in real time using a detection sensor, a rotating body, and a directional shield for radioactive pollutant detection. The rotational-based detection device is configured to check the dose rate and direction using the location information of the rotator and measurement value. We proposed a measurement technique for vertical and horizontal directions through multiple holes. It was confirmed that the measurement error for direction information was less than 1% when detected in the horizontal direction.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.140-147
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• 2021

EEG(electroencephalogram) are measured to accurately determine the level of sleep in various sleep examinations. In general, measurements are more accurate as the number of sensor channels increases. EEG can interfere with sleep by attaching electrodes to the skin when measuring. It is necessary for self sleep care to select the minimum number of EEG channels that take into account both the user's discomfort and the accuracy of the measurement data. In this paper, we proposed a sleep stage analysis model based on machine learning and conducted experiments for using from one channel to four channels. We obtained estimation accuracy for sleep stage as following 82.28% for one channel, 85.77% for two channels, 80.33% for three channels and 68.87% for four channels. Although the measurement location is limited, the results of this study compare the accuracy according to the number of channels and provide information on the selection of channel numbers in the EEG sleep analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.766-773
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• 2021

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

• Journal of Drive and Control
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• v.19 no.4
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• pp.19-28
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• 2022

This paper introduces an automatic steering system for straight traveling capable of being mounted on drivable agricultural machinery which user can handle it such as a tractor, a transplant, etc. The modular automatic steering device proposed in the paper is composed of RTK GNSS, IMU, HMI, hydraulic valve, and wheel sensor. The path generation method of the automatic steering system is obtained from two location information(latitude and longitude on each point) measured by GNSS in advance. From HMI, a straight path(AB line) can be created by connecting latitude and longitude on each point and the device makes the machine able to follow the path. During traveling along the reference path, it acquires the real time position data every sample time(0.1s), compares the reference with them and calculates the lateral deviation. The values of deviation are used to control the steering angle of the machine using hydraulic valve mounted on the axle of front wheel. In this paper, Pure Pursuit algorithm is applied used in autonomous vehicles frequently. For the analysis of traveling characteristics, field tests were executed about these conditions: velocity of 2, 3, 4km/h which is applied to general agricultural work and ground surface of solid(asphalt) and weak condition(soil) such as farmland. In the case of weak ground state, two experiments were executed about no-load(without work) and load(with work such as plowing). The maximum average deviations were presented 2.44cm, 7.32cm, and 11.34cm during traveling on three ground conditions : asphalt, soil without load and with load(plowing).

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.1-8
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• 2021

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.